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Chinese Holiday Makers' Expenditure: Implications forMarketing and Management
Author
Wang, Ying, Davidson, Michael
Published
2010
Journal Title
Journal of Hospitality Marketing & Management
DOI
https://doi.org/10.1080/19368621003667101
Copyright Statement
© 2010 Routledge. This is the author-manuscript version of this paper. Reproduced inaccordance with the copyright policy of the publisher. Please refer to the journal website foraccess to the definitive, published version.
Downloaded from
http://hdl.handle.net/10072/32237
Griffith Research Online
https://research-repository.griffith.edu.au
Chinese holiday makers expenditures Page 1 of 41
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CHINESE HOLIDAY MAKERS’ EXPENDITURE: IMPLICATIONS
FOR MARKETING AND MANAGEMENT
Chinese holiday makers expenditures Page 2 of 41
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ABSTRACT
Tourist destinations are more interested in attracting high-yield tourists and visitor
expenditure has often been used as a measure of market yield. This study examined Chinese
holiday travellers’ expenditure in Australia with the purpose of identifying the characteristics
of the high-spending segments in this market. A questionnaire was designed to collect data
from departing Chinese tourists. The study concluded that Chinese holiday travellers’ total
and disaggregated expenditures were associated with different sets of socio-demographic, trip
characteristics and psychological factors. In particular, their total expenditure in Australia
was determined by their income, age, place of residence, travel party size, length of stay and
visitation to other destination. The study extended the existing literature on tourist
expenditure. It also provided practical marketing and management implications for Australia.
KEYWORDS: Chinese holiday market to Australia, tourist expenditure
Chinese holiday makers expenditures Page 3 of 41
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CHINESE HOLIDAY MAKERS’ EXPENDITURE: IMPLICATIONS
FOR MARKETING AND MANAGEMENT
INTRODUCTION
“Tourism demand affects all sectors of an economy” (Sinclair & Stabler, 1997, p.15) and it is
“the foundation on which all tourism-related business decisions ultimately rest” (Song &
Witt, 2000, p.1). Investigation of tourist expenditure is critical because it is an indicator of
tourism demand and yield of a market. Additionally, tourists may be segmented and marketed
based on their expenditure. Expenditure can be examined at a macro or micro level. Studies
at the macro level are concerned with the analysis of aggregated expenditure in a destination
by a market, whilst most expenditure studies at the micro level examine the important factors
that affect individual tourists’ expenditures on the trip. Although the two types of expenditure
studies serve different purposes, the studies at the micro level have the advantage of taking
into account the diversity and heterogeneity of consumer behaviours that are averaged out in
macro-economic analysis. These studies also do not deviate too far from theoretical consumer
behaviour frameworks (Alegre & Pou, 2004).
A review of literature presented in this study suggested more emphases to be placed on first
the investigation of individual travellers’ expenditure, and second the impact of non-
economic and psychological factors on expenditure. Literature also suggests a clear
insufficiency of research on Chinese outbound tourism (Chon, 2005) and the economic
impact of Chinese outbound tourism (Chen, Guo, Wang & Wang, 2005). Cai and Knutson
(1998) and Cai, Hu, and Feng (2001) modeled the demand of Chinese for domestic tourism
and Qu and Lam (1997) analysed their cross border travel demand to Hong Kong. All these
studies used aggregated data. Understanding Chinese travellers’ expenditure during long haul
Chinese holiday makers expenditures Page 4 of 41
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international travel at the individual tourist level remains an under-researched area. The
purpose of this study is to fill this knowledge gap by offering an analysis into the expenditure
of Chinese travellers to Australia. More specifically, this study investigates firstly Chinese
holiday travellers’ spending pattern in Australia, secondly the determining factors of their
expenditure, thirdly the impact of satisfaction on expenditure, and fourthly the associated
managerial and marketing implications. The paper reviewed the existing research on tourist
expenditure, as well as its relationships with visitor satisfaction and destination marketing. A
questionnaire designed based upon the literature was used to collect Chinese traveller’s social
demographics, trip characteristics, satisfaction with the trip, and expenditures on various
travel related goods and services in Australia. A number of bivariate and multivariate
analytical techniques were used to examine Chinese travellers spending patterns in Australia
and how their expenditures were affected by the economic, social-demographic and
psychological factors. The study suggested that an expenditure-based segmentation of the
Chinese holiday market to Australia may be feasible and a number of implications are
provided for Australian destination marketers and managers.
A REVIEW OF STUDIES ON TOURIST EXPENDITURE
Understanding tourist expenditure is critically important in measuring tourism’s economic
impact on the destination because tourism is an expenditure-driven economic activity
(Frechtling, 2006). Expenditure studies relevant to this research may be classified into two
groups. One group of studies were carried out by tourism economists who focused on
modelling individual travellers’ expenditure. Another group of studies explored the
usefulness of expenditure as a market segmentation variable. Such a segmenting method can
help maximizing the economic benefit for tourist destinations. Additionally, satisfaction may
also influence the level of expenditure. The follow literature review is organised into three
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sub-sections: expenditure-based market segmentation, micro-economic modelling of tourist
expenditure, as well as expenditure and satisfaction.
Expenditure-based market segmentation
Tourism has become a global phenomenon and its marketing is becoming more and more
complex and costly. Destination promotional organisations are under increasing pressure to
use a segmenting approach that is effective and efficient. Marketing research suggests that
although people with high expenditure account for a disproportionately large percent of sales,
they are often indistinguishable from those of lower expenditure in terms of economic and
social demographic characteristics, and benefit sought. This increases the difficulty of
targeting this group of people (Spotts & Mahoney, 1991). However, more recent findings
indicate the utility of expenditure-based market segmentation, as shown in Legohérel (1998),
Moufakkir, Singh, Moufakkir-van der Woud, and Holecek, (2004), and Spotts and Mahoney
(1991).
According to Kotler (1988) and Spotts & Mahoney (1991) successful marketing
segmentation must exhibit four basic characteristics, namely:
• Measurability (the degree to which the size and purchasing power of all segments can
be measured);
• Substantiality (the degree to which the segments are large and/or profitable enough);
• Actionability (the degree to which effective programs can be formulated for attracting
and serving the segments); and
• Accessibility (the degree to which the segment can be effectively reached and served).
The studies by Spotts and Mahoney (1991) and Moufakkir et al. (2004) analysed the
expenditure-based market segmentation according to the above-listed characteristics and both
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studies demonstrated that such an approach holds some promise as a potential segmentation
method for destinations. Spotts and Mahoney (1991) found that “heavy spenders” were more
likely to be middle-income families travelling in a large travel party in which children are
often present. They also stayed significantly longer and participated more heavily in
recreation than “light spenders”. Legohérel (1998) found the opposite findings with regard to
the high spending travellers by stating “the groups of three or more individuals that included
children spent significantly less than childless couples” (p. 30). Moufakkir et al. (2004)
examined visitors’ spending in a gaming destination finding that “heavy spenders” were often
travelling from outside of the state, and were younger, more affluent, and more likely to stay
in hotels or motels. Mok and Iverson (2000) also successfully segmented Taiwanese tourists
to Guam using the expenditure criterion. Longer stay, younger age, smaller party size, and
honeymooners were some of the characteristics of “heavy spenders” whilst income, marital
status, gender or occupation could not be used to distinguish travellers with different levels of
spending. It is evident that expenditure-based segmentation offers a solution to maximise the
returns from marketing investment by targeting tourists having comparatively high
expenditure (Laesser & Crouch, 2006).
Micro-economic modelling of tourist expenditure
Comparing to studies using expenditure as the segmenting variable, micro-economic
modelling of tourist expenditure provides useful information on what variables are associated
with high expenditure and also on the extent to which each of the variables can influence the
expenditure. However, “the majority of (tourism demand) studies have been macro-economic
in nature, …Micro-economic studies of individual or household tourism behaviour are rare”
(Crouch, 1994, p. 41; Lim, 2006). An extensive literature search found the following micro-
economic studies on trip expenditure: Agarwal and Yochum (1999, 2000), Asgary, De Los
Santos, Vincent, & Davila (1997), Aguilo Perez and Juaneda Sampol (2000), Cannon and
Chinese holiday makers expenditures Page 7 of 41
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Ford (2002), Jang, Cai, Morrison and O’Leary (2005), Downward and Lumsdon (2000, 2003,
2004), Jang, Bai, Hong, and O’Leary (2004) , Laesser and Crouch (2006), Leones, Colby,
and Crandall (1998), Mak, Moncur, and Yonamine, (1977), Seiler, Hsieh, Seiler, and Hsieh
(2002), Taylor, Fletcher, and Clabaugh, (1993), and Wang, Rompf, Severt and Peerapatdit
(2006).
Trip expenditures have been measured in terms of total expenditure, expenditure per person
per day, total party expenditure, party expenditure per day, pre-paid expenditure in the origin
country, and expenditure in the destination. For package tourism destinations, it is necessary
to separate expenditures incurred in the origin country from those at the destination, as did
Aguilo Perez and Juaneda Sampol (2000). In order to provide more insightful implications
for individual tourism-related sectors, Wang et al. (2006) disaggregated trip expenditure into
six categories: lodging, meals, attractions, entertainment, shopping, and transportation. This
allows the investigation into the degree to which a particular factor influences different
spending categories.
Theoretically, a great variety of economic, social and psychological variables may influence
tourism demand (Ryan, 2003). Most expenditure studies included income as an independent
variable, which was found to be significant except in Downward and Lumsdon (2000) and
Leones et al. (1998). Income was often measured as a categorical variable instead of a
continuous variable. The effect of income was sometimes measured using dummy variables
(e.g. Cannon & Ford, 2002; Jang et al., 2004; Taylor et al., 1993). Only four studies
attempted to examine the impact of price on expenditure by incorporating proxy variables
such as relative price (Asgary et al., 1997), perception about price (Aguilo Perez & Juaneda
Sampol, 2000), lodging reservation and weekend accommodation (Agarwal & Yochum,
2000), and airfare and staying in hotel (Mak et al, 1977). The results of these studies
Chinese holiday makers expenditures Page 8 of 41
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suggested a significant impact of price on expenditure. Price variable has often been omitted
in cross sectional demand studies because it was assumed that all individuals being studied
face identical prices. By doing this, the difference in behaviours can be explained by the
difference in individuals’ characteristics (Deaton & Muellbauer, 1980).
The expenditure is also affected by travellers’ social demographic characteristics. Agarwal
and Yochum (1999) and Leones et al. (1998) found that age did not affect tourist expenditure.
On the contrary, older travellers from Japan to the United States were found to spend more
than their younger counterparts (Jang et al., 2004), whilst Wang et al. (2006) suggested a
negative relationship between total expenditure and the age of travellers. In contrast, Mak et
al. (1977) found middle-aged American travellers had a higher expenditure in Hawaii on a
daily basis, but stayed significantly shorter than young and aged travellers. In addition, age
may not act independently but may work with other socio-demographic characteristics (e.g.
the number and age of the male or female adults in the travel party) to influence the level of
expenditure (Downward & Lumsdon, 2000). Gender was not associated with the level of
spending (Agarwal & Yochum, 2000; Jang et al., 2004). Those who are not married were
found to spend more than those that are in Mak et al. (1977), but the opposite was found by
Asgary et al. (1997). However, two more recent studies conducted by Cannon and Ford
(2002) and Wang et al. (2006) suggested that marital status did not influence the level of
spending.
Trip characteristics, such as travel party size, length of stay, and first-time/repeat visitors
have also been frequently used to explain expenditure. An increase in travel party size
resulted in an increase in total travel expenditure (Agarwal & Yochum, 1999), but a decrease
in total expenditure per person per day (Taylor et al., 1993). As children are not income
Chinese holiday makers expenditures Page 9 of 41
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earners, number of children in the travel party was negatively related to total party
expenditure (Agarwal & Yochum, 1999). However, Wang et al. (2006) found that number of
children did not affect total expenditure. Instead, number of adults in the travel party
positively influenced total expenditure. In contrast, Jang et al. (2004) argued that it was not
number of adults, but whether the traveller had companions or not affected total spending.
Length of stay at the destination can also significantly influence travellers’ expenditure
(Agarwal & Yochum, 1999; Downward & Lumsdon, 2004; Taylor et al., 1993; Wang et al.,
2006). Its impact was positive on total tourist expenditure (Agarwal & Yochum, 1999;
Downward & Lumsdon, 2004), but negative on daily personal tourist expenditure (Taylor et
al., 1993). Wang et al. (2006) and Mak et al. (1977) found that expenditure did not differ
between first-time and repeat visitors whilst Jang et al. (2004) suggested that repeat visitors
tend to spend less on shopping than first-time visitors. Package tourists were found to have an
expenditure 10 percent lower than the average of all tourists to Australia (Laesser & Crouch,
2006).
The above review indicates that income, socio-demographic and trip-related characteristics
are by far the most commonly used variables in explaining individuals’ demand for tourism
products. In general, very few studies have attempted to investigate the impact of
psychological and supply-related factors on travellers’ expenditure, although theoretically,
these variables may also affect how much people spend. Multiple regression analysis has
been the most commonly used modelling technique. However, the models were often not
able to sufficiently explain the level of expenditure, with an explanatory power below 20
percent. This strongly suggests a need to search for new variables that can improve the
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predictability of the expenditure function. The following section discusses the possible
impact of satisfaction on expenditure, one of the focuses of the present study.
Expenditure and satisfaction
Satisfaction has been a long-standing focal point for tourism marketing due to its impact on
travellers’ post-trip behaviour and future decisions on travel; in other words, an individual’s
future demand for travelling to a destination (i.e., Heung, Wong, & Qu, 2002; Kau & Lim,
2005; Lee, Graefe & Burns, 2004). However, would satisfaction also influence the current
demand, such as an individual’s level of expenditure during a trip? Theoretically, the
satisfaction one derives from consumption impacts upon how one spends money. Business
literature has demonstrated that customer satisfaction has been an important focus of business
strategies due to its positive link to financial performance and economic return for the
businesses (e.g. Anderson, Fornell & Rust, 1997; Anderson, Fornell & Lehmann, 1994;
Reichheld & Sasser Jr, 1990). This is because satisfied customers are willing to pay higher
prices, which subsequently increases the revenue and profit.
Customers are willing “to pay more for a product or service which precisely matches their
needs” (Hill & Alexander, 2006, p. 220). Equity theory suggests that consumers seek to
maintain equity between their inputs and outputs in an exchange process. Based on this
theory, a highly satisfied customer expects high outcome from an exchange and is willing to
pay more to re-establish equity whilst a highly dissatisfied customer would want to pay less
(Homburg, Koschate, & Hoyer, 2005). The disappointment theory also indicates that the
satisfaction/dissatisfaction is a result of positive/negative disconfirmation between
expectation and perception and this process generates additional values (positive or negative)
to the consumption or usage experience (Homburg et al., 2005). Nevertheless, it is not certain
with respect to whether intention/willingness does generate purchase behaviour. It is
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therefore important to directly test the relationship between satisfaction and actual purchase
behaviour/expenditure occurred.
Emotion may arouse or be aroused by satisfaction. Expectancy/anticipation, as an emotional
factor, forms the basis for expectancy confirmation/disconfirmation, thus affects satisfaction
in a consumptive situation (Holbrook, 1986). Satisfaction response may be in the emotional
modes of contentment, pleasure, delight, relief and ambivalence (Arnould, Price, & Zinkhan,
2004), and more pleasure experienced during consumption leads to higher satisfaction (Wirtz
& Bateson, 1999). A number of studies in retailing literature have explored the effect of
emotion and satisfaction on expenditure, which generated mix results. Evidence showed that
emotion had significant and direct influence of shoppers’ expenditure of time and money at
the shopping mall and a good mood is associated with higher expenditure at the mall (Babin
& Darden, 1995 & 1996). Shim and Eastlick (1998) also found that shoppers who held
favourable attitudes toward the mall’s attributes are more likely to spend at the mall.
However, Stoel, Wickliffe, and Lee (2004) argued that, although higher satisfaction led to an
increase in time spent at the mall, it did not necessarily increase the level of expenditure at
the mall. Additionally, the overall satisfaction with the shopping trip positively correlated
with shoppers’ perceptions of hedonic and utilitarian value resulting from their trip, which is
also positively correlated with level of shopping expenditure (Babin, Darden, & Griffin,
1994).
The behaviour of international travellers takes place in a much broader context than a
shopping trip to a regional mall. For this reason, in the context of international tourism, the
impact of a wider range of factors may need to be taken into account when modelling
expenditure. However, the above-mentioned studies imply emotional factors and satisfaction
Chinese holiday makers expenditures Page 12 of 41
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as potential determinants of tourist expenditure in a destination, especially considering two
reasons. According to Fornell and Rust (2005), service quality is less standardized and
consistent than the quality of tangible goods. Consequently, changes in customer satisfaction
will have a greater impact on customers’ spending on services than on tangible goods. Based
on a meta-analysis of existing literature on customer satisfaction, Szymanski and Henard
(2001) expressed a similar view by emphasising the importance of distinguishing intangible
services from tangible as satisfaction plays a stronger role in decisions to buy intangible
services. International travel to a destination involves many repeat purchases and ongoing
service commitments. Cumulative satisfaction based on repeated experience has a stronger
impact on consumption than transaction-specific satisfaction based on a single experience
(Homburg et al., 2005). An example would be Chinese travellers' to Australia purchasing
souvenirs and duty free goods in every city on their itinerary. It is reasonable to assume that
the level of satisfaction with the first consumption experience in Australia has a strong impact
on travellers’ spending behaviour during the rest of the trip. Such effect would be
strengthened toward the end of their stay in Australia.
RESEARCH METHOD
Questionnaire design
Based upon the literature review, it is proposed that Chinese holiday travellers’ expenditure
in Australia is affected by their income, socio-demographics, trip characteristics and
satisfaction with the trip. It was assumed that travellers face the same price in Australia;
therefore, price impact was not measured in this study. Although the ‘International Visitor
Survey’ conducted annually by Tourism Australia may capture the most representative
sample for inbound tourism to Australia, the survey was not specifically tailored to suit
different inbound markets and research purposes (e.g., lack of data on income). Therefore, a
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self-designed questionnaire was used to collect data on Chinese holiday travellers, which
include:
• total and disaggregated expenditures on various categories of tourism products;
• income and social demographic characteristics including gender, age, place of
residence, marital status, level of education, occupation, annual income, and
dependent children;
• trip characteristics such as first/repeat visitor, number of nights spend in Australia,
stop over in other destinations on the way to Australia or on the return; and
• satisfaction with the overall trip and various components of the trip including
accommodation, food and drink, tourist attractions, shopping, air transportation, tour
itinerary, transfer between sites, tour guide, and other leisure activities (measured on a
5-point Likert Scale with 1 being ‘strongly dissatisfied’ through to 5 being ‘strongly
satisfied’).
The questionnaire consists of mostly factual questions where the range of answers to a
question is limited and pre-coded questions are generally preferred (Moser & Kalton, 2004).
Decisions on the pre-coded answers consulted previous studies focusing on the Chinese
outbound travel market as well as the official statistics released by both the Australian and
Chinese governments. For instance, place of residence has ten pre-coded categories that
include the nine regions covered by the Approved Destination Status (ADS) operation at the
time the study was conceptualised, plus a category for other areas. Age was measured in unit
of 5 years from 15–19 to 70 and over. For each category to receive enough respondents, the
pre-coded answers were collapsed into fewer categories in data analysis.
The sample and survey administration
Although the theoretical population of the survey includes all Chinese holiday tourists to
Australia, it was impossible to draw a large national sample across different Australian states,
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given the limited research resources. Additionally, accurate tourist expenditure data can only
be collected at the end of visitors’ trips after the consumption has finished. The study thus
decided to focus on the accessible population of Chinese holiday tourists departing from
Brisbane. The survey was conducted in the Brisbane International Airport during a three
week period. Departing Chinese travellers were approached randomly for their voluntary
participation in the study. In total, 380 usable questionnaires were collected.
Data analysis techniques
The bivariate analysis of correlation, independent sample t-test and ANOVA were used to
examine the individual effect of various social-demographic characteristics, trip
characteristics, and satisfaction on travellers’ expenditure in the preliminary analysis stage.
Then, the multiple regression analysis was performed to confirm the results of bivariate
analyses, and to show the collective effect of independent variables on expenditure.
FINDINGS
Trip expenditures
Table 1 reports Chinese travellers’ total and disaggregated expenditures. Expenditures were
measured in Australian dollars. The results revealed that the average total expenditure per
person per trip by Chinese tourists is $4,658 and the cost of tour package averaged $3,154.
With regard to Chinese tourists’ expenditure in Australia, the average is $1,426. The
coefficient of variation (CV), a proportionate measure of variability that allows for
comparison of relative variability of more than one data set, indicated that total expenditure
in Australia has the largest relative variability whilst tour package has the smallest variability.
On average, Chinese tourists spent $166 or 22 percent of their total expenditure in Australia
on food and drink during their stay in Australia. They also spent $887 on shopping to take
home, $349 on gambling/entertainment, and $179 on cultural/sporting activities. The large
values for standard deviation indicate a high variability in travellers’ expenditure.
Chinese holiday makers expenditures Page 15 of 41
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Insert Table 1 here
Expenditures by traveller characteristics
Table 2 to Table 4 report the characteristics of the sample and the expenditures by those
characteristics. Five expenditure categories are reported: total expenditure per person in
Australia, and expenditure per person on shopping, cultural/sporting activities, food/drinks,
and gambling/entertainment. Preliminary analysis using bivariate techniques found
significant differences in the expenditures of travellers of different socio-demographic and
trip characteristics. These significant differences are marked in the tables with asterisks. In
the preliminary analysis, the expenditure data were log transformed to satisfy the normality
assumption of the analytical tests performed.
Insert Table 2 here
There are slightly more males (56.6%) than females (43.4%) in the sample. About 64.9% of
the participants are aged between 30 and 49. Three-quarters of the visitors are married, and
among 277 married travellers, about three-quarters have dependent children. Chinese tourists
aged between 30 and 49 had a significantly higher total expenditure than those aged below
30. The expenditure difference between the two groups is $456. The expenditure on
gambling/entertainment of those who have a dependent child is $241 higher than those who
do not have. Chinese tourists’ expenditures on shopping, cultural/sporting activities and
food/drink were not affected by the dependent child factor, neither was their total expenditure
in Australia. The results suggest no difference in visitors’ total and disaggregated
expenditures between single and married visitors.
Table 3 reports Chinese travellers’ expenditure by place of residence, education level,
occupation and income. Nearly 80% of the travellers have tertiary education or above. An
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ANOVA test suggested that both people with senior middle school qualification ($191) and
people with undergraduate degree ($300) spent less on gambling/entertainment than people
having junior middle school qualification or below ($940).
Insert Table 3 Here
Four main places of origin in this sample are Beijing, Shanghai, Guangdong and Zhejiang,
which together contributed more than two-thirds of the respondents. The total expenditure of
visitors from Zhejiang province is $979 higher than that of Guangdong residents. With regard
to occupation, business owners, managers and professionals ranked as the top three and
jointly accounted for 63.8% of the total respondents. Government official, clerk, plant and
machine operator and assembler, retired/unemployed categories were classified with all other
occupations to form the “Other” category. Altogether, these professions represent 20.4% of
the sample. As shown in the table, Chinese managers ($1424) spent significantly more on
shopping than professionals ($699). Professionals ($94) spent less on food and drink than
other occupations ($276).
About 21% of the visitors have an income above ¥300,000 and visitors with income below
¥100,000 account for 48.6% of all the survey participants. As indicated in the table, total
expenditure and expenditure on cultural/sporting activities differed across different income
groups. The income group of above ¥300,000 spent $1055 more per head in total than the
below ¥100,000 income group. Regarding expenditure on cultural/sporting activities, the
below ¥100,000 income group ($112) spent significantly less than the other two income
groups ($209).
Chinese holiday makers expenditures Page 17 of 41
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Expenditures by trip characteristics
As shown in Table 4, first-time travellers dominated the sample (92.2%). Travellers who
visited Australia for the first time ($354) spent significantly less on gambling/entertainment
than repeat visitors ($899). However, this result needs to be interpreted with caution due to
the small sample size (7) of repeat visitors.
Insert Table 4 here
The numbers of nights in Australia were grouped into three categories: 6 nights and under, 7
to 8 nights and 9 nights and over. Differences existed in the total expenditure, expenditure on
shopping, gambling/entertainment and food/drink across travellers of different lengths of
stay. The highest expenditure occurred in the category of seven to eight nights. Travel party
size also had a significant impact on visitors’ total expenditure and expenditure on shopping
and gambling/entertainment. For instance, in terms of total expenditure, those who travelled
individually ($2126) spent significantly more than those who travelled in groups of three
($1351) and four or more ($840). On their trip to Australia, two-thirds of the Chinese tourists
visited countries/destinations other than Australia. There is a significant difference in the total
spending between travellers who visited Australia only ($1343) and those who visited
multiple destinations ($1802).
Expenditure and satisfaction
Overall satisfaction was measured by a compound variable: the average score of the overall
trip and trip elements. Using a compound variable “reduces the measurement error by using
multiple indicators to reduce the reliance on a single response”, and has the “ability to
represent the multiple aspects of a concept in a single measure” (Hair, Anderson, Tatham, &
Black (1998, p. 116, 117). The correlation analysis performed between total expenditure and
overall satisfaction produced a significant but low coefficient of -0.169 (p<0.01). The
Chinese holiday makers expenditures Page 18 of 41
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negative coefficient seems to suggest a decreasing expenditure in association with an
increasing level of satisfaction.
Regression analysis results
A regression analysis using ordinary least squares (OLS) estimation method was performed
on total expenditure as the dependent variable and its determinants as the independent
variables. The expenditure was log transformed to satisfy the normality assumption. This can
also remove the outliers and deal with the heteroskedasticity problem (Downward &
Lumsdon, 2004). Two regression models were estimated. The first model includes all the
social demographic, trip-related and satisfaction variables whereas the second model takes
account of only those variables tested significant in the preliminary analysis (income, age,
place of residence, travel party size, length of stay, single/multiple destinations, and
satisfaction). The second model reported in Table 5 has a higher adjusted R square value and
is free of multicollinarity. The independent variables in the regression model were measured
in the natural units. Dummy variables were created for each categorical variable using
indicator coding. In such coding, K-1 dummy variables are created to represent a categorical
variable with K levels. The effect of the omitted level (also called the reference category) is
captured by the constant term in the regression model. The regression coefficients for the
dummy variables represent the difference on the dependent variable for each level of the
variable from the reference category (Hair, Black, Babin, Anderson, & Tatham, 2005). The
reference group in this analysis consists of visitors aged below 30, residing in Zhejiang
province, visited multi-destination, stayed in Australia for more than 8 nights, and having an
annual income of more than ¥300,000.
Insert Table 5 here
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There is an overall relationship between total expenditure per person in Australia and the
independent variables, given that the overall model is significant, with F (12, 203) = 6.645, p
< 0.001. The model has an adjusted R square of 0.254 suggesting that all the independent
variables together explained 25.4 percent of the variation in visitors’ expenditure. This is a
satisfactory level of explanatory power given that the study used the cross-sectional data,
which, according to Asgary, De Los Santos, Vincent, and Davila (1997) would yield much
lower R square compared to time series data.
Apart from the constant, four independent variables are significant at the 5 percent level and
four other variables are significant at the 10 percent level, indicating they had considerable
impact on the total expenditure per person in Australia. These variables are travel party size
and dummy variables for age 30 to 49, place of residence in Beijing, visiting another
destination, 6 nights and under, 7 to 8 night, income below ¥100,000, and income between
¥100,000 and ¥300,000. The independent variable of overall satisfaction is not significant.
Among the independent variables, travel party size contributes the most to the variation in the
expenditure, given the largest magnitude in terms of the standardized coefficient.
The regression analysis involves using log-transformed dependent variable (also called semi-
log regression equation), in which the coefficient for a continuous variable is interpreted as
the percentage change in dependent variable for a unit change in the independent continuous
variable. Taking travel party size as an example, the regression coefficient is -.333, thus the
total expenditure per person in Australia is expected to decrease by 33.3 percent given an
additional person in the travel party. For dummy variables in the semi-log functional form,
the percentage impact of a dummy variable on the dependent variable is calculated using the
formula below
Chinese holiday makers expenditures Page 20 of 41
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)1)2/)((exp(100 −−= bVbg (1)
Where g is the percentage impact of the dummy variable on the dependent variable; b is the
regression coefficient for the dummy variable; V(b) is the estimated variance of the
regression coefficient for the dummy variable (Halvorsen & Palmquist, 1980).
Using formula (1), the percentage impacts of the significant dummy variables on the
dependent variable of total expenditure per person in Australia were calculated and presented
in the far right column of Table 5. For the dummy variable of age 30 to 49, the result can be
interpreted as Chinese holiday tourists aged between 30 and 49 spent 38.8 percent more than
those aged under 30 (the reference category) without taking into account the effects of other
independent variables. This result is not surprising as travellers under 30 years old are less
established career-wise, earn less money, and have less saving. This age cohort also includes
student travellers who were funded by their parents and subsequently had a less flexible
travel budget. Residents of Beijing spent 38.3 percent less than those of Zhejiang. A multiple
destination tour package costs substantially more than a single destination package that may
imply a higher affordability of multiple destination travellers as compared to travellers who
visited Australia only. As a result, multiple-destination travellers spent 23.3 percent more in
Australia than those who visited Australia only. With regard to the length of stay in Australia,
the reference group of 8 nights and more had an average expenditure that is 29.6 percent
higher than the short stay group (6 nights and under), but is 40.9 percent lower than people
stayed who 7 or 8 nights. The reason behind this phenomenon may be associated with the
travel itinerary and the standard of the package. The effect of the income is as expected.
Travellers’ of high income spent 38.8 and 31.6 percent more than the low and middle income
travellers. Diagnostic check of multicollinearity using tolerance and variance inflation factors
(VIF) are presented in Table 5, showing no concern of multicollinearity problem in the
Chinese holiday makers expenditures Page 21 of 41
21
regression analysis. Other diagnostic check results show that the assumptions of linearity,
normality and multivariate outliers are also satisfied.
Further analysis on expenditure and satisfaction
The results of further analysis using ANOVA on overall trip experience in relation to total
expenditure in Australia are displayed in Table 6. Satisfaction levels that received fewer than
five responses were excluded from the analysis. The ANOVA obtained a significant F
statistic (F (2,219) = 5.649, p < 0.01). The multiple comparisons show that travellers who
were strongly satisfied ($890) were found to spend significantly less than those who stated
“neutral” feeling with their overall trip experience ($2086).
Insert Table 6 here
An ANOVA was performed on levels of satisfaction with shopping in relation to shopping
expenditure. A significant F value (F (4,206) = 4.257, p = 0.025) was obtained and the
figures suggest that tourists having high spending on shopping were either satisfied or
strongly dissatisfied (see Table 7). The multiple comparisons show that those tourists who
were satisfied with shopping ($1416) spent significantly more on shopping than neutrally
satisfied ($815) and dissatisfied tourists ($619).
Insert Table 7 here
DISCUSSION AND IMPLICATIONS
At the individual level, direct tourist expenditure is the most commonly used indicator of a
tourist’s contribution to the destination’s economy and the expenditure can vary very widely
from one traveller to another. This study revealed an average of $217 per night spending in
Australia by Chinese travellers for holiday purposes as compared to $82 by all Chinese
travellers, $90 by all international travellers in 2005 (Bureau of Tourism Research, 2000-
2005), and an average daily expenditure of $104 by Chinese business travellers in Australia
(Tourism Australia, 2006a; 2006b). This suggests that on a daily basis, Chinese holiday
Chinese holiday makers expenditures Page 22 of 41
22
travellers make a higher economic contribution than other market segments and therefore
should attract more marketing efforts.
The literature shows that expenditure-based segmentation is viable and practical (Spotts &
Mahoney, 1991; Pizam & Reichel, 1979). People who have high expenditure can be
distinguished from those who have low expenditure in terms of economic and social
demographic characteristics (Mudambi & Baum, 1997) and trip-related characteristics (Spotts
& Mahoney, 1991). Identifying high-yield market segment is particularly important for
destinations when operating in a mass tourism market like China. The Chinese holiday travel
market is dominant by pre-paid package travel, which is commonly associated with high
expenditure leakage due to the fact that packages were purchased before the trip and a
significant proportion of the expenditure on package stays in the origin country. A feasible
strategy to maximize the economic benefit from the Chinese holiday market is to attract those
tourists who have high expenditure during their stay in the destination.
This study examined the spending pattern of Chinese holiday travellers to Australia and
investigated the factors determining their expenses occurred in Australia. There was a huge
variation in Chinese holiday tourists’ expenditure, suggesting the market may be segmented
according to the volume of spending. The study revealed that Chinese travellers’ total and
disaggregated expenditures in Australia varied across people of different socio-demographic
background and trip characteristics, as summarized in Table 8.
Insert Table 8 here
Chinese visitors’ total expenditure in Australia varied according to their income, age, place of
residence, travel party size, length of stay, and visitation to other destination(s), among which
Chinese holiday makers expenditures Page 23 of 41
23
travel party size and length of stay seemed to influence the level of expenditure to a greater
extent than other variables. With respect to the difference in expenditures on shopping,
occupation, travel party size and length of stay were the contributing factors. Expenditure on
cultural and sporting activities was only affected by visitors’ income and visitation to other
destination(s). Two variables, occupation and length of stay influenced Chinese visitors’
expenditure on food and drinks. In addition, the factors of dependent child, education level,
travel party size, length of stay, and first/repeat visit significantly affected visitors’
expenditure on gambling and entertainment. In contrast, gender and marital status had the
least impact on visitors’ level of spending.
The identification of the relationships between Chinese travellers’ expenditure and their
socio-demographics and trip-related characteristics provides information to Australia’s
destination marketers in regard to variables that can help identify the high yield segments in
this market. A heavy spender in terms of total expenditure is a sole traveller earning more
than ¥300,000 a year, aged between 30 to 49 years, residing in Zhejiang province, staying in
Australia for 7 to 8 days, and visiting a secondary destination in addition to Australia. This is
the segment that Australia, as a destination, should pursue. The high yield shopping segment
consists of travellers who hold a managerial position, travel alone and stay for 7 to 8 nights.
Travellers having high expenditure on cultural and sporting activities usually visit multiple
destinations and earn more than ¥300,000 per annum. A big spender on food and drink has a
length of stay of 7 to 8 nights and is not a business owner, manager, professional, or student.
The gambling and entertainment sector should focus on tourists who are repeat visitors,
travelling alone, having dependent child, not well-educated, and staying for 7 to 8 night.
Chinese holiday makers expenditures Page 24 of 41
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To cater for different segments, differentiated products are needed. However, this study
revealed that tour packages are homogenous in terms of price. It may be assumed that the
packages are highly standardised and little effort has been put into market segmentation. With
limited options, Chinese travellers with different purchasing power and expectations were
forced into similar packages. This may have resulted in the huge variation in expenditures on
products not included in the packages, such as shopping. Appropriate research needs to be
conducted with respect to high yield Chinese visitors’ preferences for tourist activities,
destinations, travel modes, etc. Effective packaging can then be achieved based on research
undertaken.
There has been anecdotal evidence in the areas other than tourism and hospitality that
emotional factors and satisfaction may influence people’s expenditure (Babin & Barden,
1995; Babin et al. 1994; Shim & Eastlick, 1998). Satisfaction is said to influence travellers’
decision to re-visit the destination and preference to recommend the destination to others. In
this sense, satisfaction can affect travellers’ future consumption/expenditure. However, there
is no empirical evidence of whether satisfaction can also affect travellers’ consumption
decisions during their trip. One of the differentiating characteristics of this study is to
investigate how satisfaction is related to tourist expenditure. The study found that expenditure
varied across different satisfaction levels, but the relationship between the two variables is
not linear as indicated by the insignificant regression analysis results. Varied level of
spending on shopping was also observed across different levels of satisfaction with shopping.
High spending travellers were either satisfied or strongly dissatisfied. Shopping was a very
important element in Chinese travellers’ tour itinerary and Chinese travellers engaged in
multiple shopping activities during the trip. Satisfaction with the first one or two shopping
activities may increase the likelihood of participating in more shopping activities. If such an
Chinese holiday makers expenditures Page 25 of 41
25
assumption is upheld, satisfaction can bring about higher expense on shopping. However, for
a small group of travellers, their high expenditure may, in fact, be the cause of dissatisfaction.
For instance, if a traveller purchased a considerable amount of duty free goods under the
influence of others (e.g., a tour guide) or if the purchase was an impulse decision, and later
he/she found out that the goods were over-priced, of poor quality, or not what he/she really
wanted, the feeling of being tricked into buying could lead to a high level of dissatisfaction.
This may explain the high expenditure by strongly dissatisfied travellers. It also validated
Weber’s claim (1997) that expenditure can affect travellers’ evaluation of the trip, especially
when travel is expensive to travellers.
CONCLUSION
In terms of the total economic value, China is currently Australia’s fourth largest inbound
tourism market (Tourism Australia, 2008) with the potential to become its largest market in
2016 (Tourism Forecasting Committee, 2007). It is unlikely that such a huge market is
homogenous and sensibly segmenting the Chinese holiday market is essential for Australia to
operate successfully in this market. This study investigated Chinese holiday travellers’
expenditure in Australia. It provided a review of tourist expenditure analyses, which
identified three major groups of variables that have been commonly included in the
expenditure studies: economic, socio-demographic, and trip-related variables. The empirical
results regarding the effect of these variables on expenditure are often in conflict, suggesting
a need for further investigation into this area. This study examined the individual and joint
effects of a selective number of economic, socio-demographic and trip-related characteristics
on level of expenditure. The results provided additional evidence into the role of these
characteristics in determining how much travellers spend. It is also the first such study
conducted for Chinese outbound travel market.
Chinese holiday makers expenditures Page 26 of 41
26
Tourist destinations are more interested in attracting high-yield tourists who have high per
capita spending than simply increase the number of tourists. This study concludes that whilst
a large proportion of Chinese travellers may be conscious of travel cost, there are segments
within this market that are relatively more affluent and less price sensitive. Chinese
travellers’ total and disaggregated expenditures were found to be associated with different
sets of social demographics, trip characteristics and psychological factors. In terms of total
expenditure, Chinese holiday travellers can be segmented and targeted based on their income,
age, place of residence, travel party size, length of stay, and visitation to other destinations.
The findings of this study may help Australia gain maximum benefit from the holiday travel
demand from China.
Although psychological variables have been recognized as important influencers of people’
travel-related decisions (Laesser & Crouch, 2006; Murphy, 1985; Wang et al. 2006), only a
limited number of tourism studies have incorporated such variables and no study in the field
of tourism and hospitality has considered the effect of visitor satisfaction on travel
expenditure. Therefore, another theoretical contribution of this study is related to its effort to
explore the effect of satisfaction on travellers’ spending behaviour. As revealed in this study,
the level of total and shopping expenditures seemed to be associated with the level of
satisfaction. The study offered the first step in examining how visitor satisfaction may affect
tourist expenditure. Future studies can expand on these results to examine the relationship
between expenditure and satisfaction using national samples or in other markets.
Additionally, due to practical reasons, this study only examined a limited number of
variables. The effect of other variables, especially psychological factors, on tourist
expenditure is a research topic of interest for future studies.
Chinese holiday makers expenditures Page 27 of 41
27
REFERENCES
Agarwal, V. B., and Yochum, G. R. (1999). Tourist spending and race of visitors. Journal of
Travel Research, 38(2), 173-176.
Agarwal, V. B., and Yochum, G. R. (2000). Determinants of tourist spending. In A. G.
Woodside, G. I. Crouch, J.A. Mazanec, M. Oppermann & M. Y. Sakai (Eds.),
Consumer Psychology of Tourism, Hospitality and Leisure (Vol. 1, pp. 311-330).
Wallingford, UK: CABI Publishing.
Aguilo Perez, E., and Juaneda Sampol, C. (2000). Tourist expenditure for mass tourism
markets. Annals of Tourism Research, 27(3), 624-637.
Alegre, J., and Pou, L. (2004). Micro-economic determinants of the probability of tourism
consumption. Tourism Economics, 10(2), 125-144.
Anderson, E. W., Fornell, C., and Lehmann, D. R. (1994). Customer satisfaction, market
share, and profitability: Findings from Sweden. Journal of Marketing, 58(3), 53-66.
Anderson, E. W., Fornell, C., and Rust, R. T. (1997). Customer satisfaction, productivity, and
profitability: Differences between goods and services. Marketing Science, 16(2), 129-
145.
Arnould, E., Price, L., and Zinkhan, G. (2004). Consumers (2nd Ed.). Boston: McGraw
Hill/Irwin.
Asgary, N., De Los Santos, G., Vincent, V., and Davila, V. (1997). The determinants of
expenditures by Mexican visitors to the border cities of Texas. Tourism Economics,
3(4), 319-328.
Babin, B. J., Darden, W. R., and Griffin, M. (1994). Work and/or fun: Measuring hedonic and
utilitarian shopping value. The Journal of Consumer Research, 20(4), 644-656.
Babin, B. J., and Darden, W. R. (1995). Consumer self-regulation in a retail environment.
Journal of Retailing, 71(1), 47-70.
Chinese holiday makers expenditures Page 28 of 41
28
Babin, B. J., and Darden, W. R. (1996). Good and bad shopping vibes: Spending and
patronage satisfaction. Journal of Business Research, 35(3), 201-206.
Bureau of Tourism Research. (2000-2005). International visitor survey. Canberra: BTR.
Cai, L. A., and Knutson, B. J. (1998). Analysing domestic tourism demand in China: A
behavioural model. Journal of Hospitality and Leisure Marketing, 5(2/3), 95-113.
Cai, L. A., Hu, B., and Feng, R. (2001). Domestic tourism demand in China's urban centres:
Empirical analyses and marketing implications. Journal of Vacation Marketing, 8(1),
64-74.
Cannon, T. F., and Ford, J. (2002). Relationship of demographic and trip characteristics to
visitor spending: An analysis of sports travel visitors across time. Tourism Economics,
8(3), 263-271.
Chen, Y., Guo, Y., Wang, K-C., and Wang, Y. (2005). An empirical study on economic
impacts of mainland Chinese outbound tourism by pleasure travellers. Paper
presented at the Fourth Annual Asia Pacific Forum for Graduate Student Research in
Tourism, August 1-3, Hawaii.
Chon, K. (2005). Opening Address for the Second China Tourism Forum and the Third
China Tourism Academy Annual Conference, December 16-17, Kunming, China.
Crouch, G. I. (1994). The study of international tourism demand: A survey of practice.
Journal of Travel Research, 33(4), 41-55.
Deaton, A., & Muellbauer, J. (1980). Economics and Consumer Behaviour. Cambridge:
Cambridge University Press.
Downward, P., and Lumsdon, L. (2000). The demand for day-visits: An analysis of visitor
spending. Tourism Economics, 6(3), 251-261.
Downward, P., and Lumsdon, L. (2003). Beyond the demand for day-visits: An analysis of
visitor spending. Tourism Economics, 9(1), 67-76.
Chinese holiday makers expenditures Page 29 of 41
29
Downward, P., and Lumsdon, L. (2004). Tourism transport and visitor spending: A study in
the North York Moors National Park, UK. Journal of Travel Research, 42(4), 415-
420.
Fornell, C., and Rust, R. T. (2005, September 9). The Effect of Buyer Satisfaction on
Consumer Spending Growth. Retrieved June 20, 2007, from
http://www.ivey.uwo.ca/Research/IRS_Papers/Rust.pdf
Frechtling, D. C. (2006). An assessment of visitor expenditure methods and models. Journal
of Travel Research, 45(1), 26-35.
Halvorsen, R., and Palmquist, R. (1980). The interpretation of dummy variables in
semilogarithmic equations. American Economic Review, 70(3), 474-475.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data
Analysis (5th ed.). Upper Saddle River, N.J.: Prentice Hall.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., and Tatham, R. L. (2005).
Multivariate Data Analysis, (6th ed.). Upper Saddle River, NJ: Pearson Education.
Heung, V. C. S., Wong, M. Y., and Qu, H. (2002). A study of tourists’ satisfaction and post-
experience behavioural intentions in relation to airport restaurant services in the Hong
Kong SAR. Journal of Travel and Tourism Marketing, 12(2/3), 111–135.
Hill, N., and Alexander, J. (2006). Handbook of Customer Satisfaction and Loyalty
Measurement. Aldershot, Hampshire, England: Gower Publishing, Ltd.
Holbrook, M. B. (1986). Emotion in the consumption experience: Toward a new model of the
human consumer. In R. A. Peterson, W. D. Hoyer, and W. R. Wilson (Eds.), The Role
of Affect in Consumer Behaviour (pp. 17-52). Lexington, MA: Heath.
Homburg, C., Koschate, N., and Hoyer, W. D. (2005). Do satisfied customers really pay
more? A study of the relationship between customer satisfaction and willingness to
pay. Journal of Marketing, 69(2), 84-96.
Chinese holiday makers expenditures Page 30 of 41
30
Jang, S. C., Bai, B., Hong, G-S., and O'Leary, J. T. (2004). Understanding travel expenditure
patterns: A study of Japanese pleasure travelers to the United States by income level.
Tourism Management, 25(3), 331-341.
Jang, S. C., Cai, L. A., Morrison, A. M., and O'Leary, J. T. (2005). The effect of travel
activities and seasons on expenditure. International Journal of Tourism Research,
7(6), 335-346.
Kau, A-K., and Lim, P-S. (2005). Clustering of Chinese tourists to Singapore: An analysis of
their motivations, values and satisfaction. International Journal of Tourism Research,
7(4/5), 231-248.
Kotler, P. (1988). Marketing Management: Analysis, Planning, Implementation, and
Control. Englewood Cliffs, NJ: Prentice Hall.
Laesser, C., and Crouch, G. I. (2006). Segmenting markets by travel expenditure patterns:
The case of international visitors to Australia. Journal of Travel Research, 44(4), 397-
406.
Lee, J., Graefe, A. R., and Burns, R. C. (2004). Service quality, satisfaction, and behavioral
intention among forest visitors. Journal of Travel & Tourism Marketing, 17(1), 73-82.
Legohérel, P. (1998). Toward a market segmentation of the tourism trade: Expenditure levels
and consumer behavior Instability. Journal of Travel and Tourism Marketing, 7(3),
19-39.
Leones, J., Colby. B., and Crandall, K. (1998). Tracking expenditures of the elusive nature
tourists of Southeastern Arizona. Journal of Travel Research, 36(3), 56-64.
Lim, C. (2006). A survey of tourism demand modelling practice: Issues and implications (45-
72). In L. Dwyer, & P. Forsyth (Eds.), International Handbook on the Economics of
Tourism. Cheltenham, UK: Edward Elgar Publishing.
Mak, J., Moncur, J., and Yonamine, D. (1977). Determinants of visitor expenditures and
Chinese holiday makers expenditures Page 31 of 41
31
visitor lengths of stay: A cross-section analysis of US visitors to Hawaii. Journal of
Travel Research, 15(3), 5-8.
Mok, C., and Iverson, T. J. (2000). Expenditure-based segmentation: Taiwanese tourists to
Guam. Tourism Management, 21(3), 299-305.
Moufakkir, O., Singh, A. J., Moufakkir-van der Woud, A., and Holecek, D. F. (2004). Impact
of light, medium and heavy spenders on casino destinations: Segmenting gaming
visitors based on amount of non-gaming expenditures. UNLV Gaming Research and
Review Journal, 8(1), 59-71.
Mudambi, R., and Baum, T. (1997). Strategic segmentation: An empirical analysis of
tourist expenditure in Turkey. Journal of Travel Research, 36(1), 29-34.
Murphy, P. E. (1985). Tourism: A Community Approach. New York: Methuen.
Pizam, A., and Reichel, A. (1979). Big spenders and little spenders in US tourism.
Journal of Travel Research, 18(1), 42-43.
Qu, H., and Lam, S. (1997). A travel demand model for Mainland Chinese to Hong Kong.
Tourism Management, 18(8), 593-597.
Reichheld, F. F., and Sasser Jr., W. E. (1990). Zero defections: Quality comes to services.
Harvard Business Review, 68(5), 105-111.
Ryan, C. (2003). Recreational Tourism: Demand and Impacts. Clevedon: Channel View
Publications.
Seiler, V. L., Hsieh, S., Seiler, M. J., and Hsieh, C. (2002). Modeling travel expenditures for
Taiwanese tourism. Journal of Travel and Tourism Marketing, 3(4), 47-61.
Shim, S., and Eastlick, M. A. (1998). The hierarchical influence of personal values on mall
shopping attitude and behaviour. Journal of Retailing, 74(1), 139-160.
Sinclair, T. M., and Stabler. M. (1997). The Economics of Tourism. London: Routledge.
Song, H., and Witt, S. F. (2000). Tourism Demand Modelling and Forecasting: Modern
Chinese holiday makers expenditures Page 32 of 41
32
Econometric Approaches. New York: Pergamon.
Spotts, D. M., and Mahoney, E. M. (1991). Segmenting visitors to a destination region based
on the volume of their expenditures. Journal of Travel Research, 29(4), 24-31.
Stoel, L., Wickliffe, V., and Lee, K-H. (2004). Attribute beliefs and spending as antecedents
to shopping value. Journal of Business Research, 57(10), 1067-1073.
Szymanski, D. M., and Henard, D. H. (2001). Customer satisfaction: A meta-analysis of the
empirical evidence. Journal of the Academy of Marketing Science, 29(1), 16-35.
Taylor, D. T., Fletcher, R. R., and Clabaugh, T. (1993). A comparison of characteristics,
regional expenditures, and economic impact of visitors to historical sites with other
recreational visitors. Journal of Travel Research, 32(1), 30-35.
Tourism Australia. (2006a, June 14). China: Visitor Profile. Retrieved September 10, 2006,
from http://www.tourism.australia.com/content/China
Tourism Australia. (2006b, October). China: Outbound Business Travel Snapshot. Retrieved
June 10, 2007, from
http://www.tourism.australia.com/content/Events/Outbound%20BT%20Snapshot/Chi
na_Travel_Snapshot.Sept2006.pdf
Tourism Australia. (2008). China: Visitor Profile 2007. Retrieved July 25, 2008, from
http://www.tra.australia.com/content/documents/Visitor%20Profile/2008/China.pdf.
Tourism Forecasting Committee. (2007). Forecast 2007 Issue 2. Canberra: Tourism Research
Australia.
Wang, Y., Rompf, P., Severt, D., and Peerapatdit, N. (2006). Examining and identifying the
determinants of travel expenditure pattearns. International Journal of Tourism
Research, 8(5), 333-346.
Chinese holiday makers expenditures Page 33 of 41
33
Weber, K. (1997). Assessment of tourist satisfaction, using the expectancy disconfirmation
theory: A study of German travel market in Australia. Pacific Tourism Review, 1(1),
35–45.
Wirtz, J., and Bateson, J. E. G. (1999). Consumer satisfaction with services: Integrating the
environment perspective in services marketing into the traditional disconfirmation
paradigm. Journal of Business Research, 44(1), 55-66.
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Table 1
Total and Disaggregated Expenditures per Person by Chinese Travellers
Total expenditure N 5%
trimmed
mean
Std.
deviation
Coefficient
of variation
Total expenditure on the trip 280 $4,658 $3,942 0.85
Expenditure on tour package 282 $3,154 $495 0.16
Total expenditure in Australia
(excluding pre-paid package)
291 $1,425
$2,883
2.02
Per night expenditure in Australia
(excluding pre-paid package)
265 $217 $421 1.94
Disaggregated Expenditure N 5%
Trimmed
Mean
Std.
Deviation
% of Total
expenditure
Food and drink 126 $166 $810 22%
Shopping to take home 220 $887 $2,773 68%
Gambling/entertainment 116 $349 $3,157 28%
Cultural/sporting activities 45 $179 $238 22%
Note: Expenditures are in Australian dollars.
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Table 2
Expenditures by Gender, Age, Marital Status, and Dependent Children
Social demographic
and trip characteristics N % Expenditure per person ($)
Total Shopping Cultural
/
sporting
Food/
drinks
Gambling/
entertainment
Gender Male 207 56.6 $1,807 $1,089 $191 $163 $421
Female 159 43.4 $1,419 $1,007 $161 $194 $308
Age ≤30 91 24.8 *$1,347 $977 $170 $163 $344
31-49 240 64.9 *$1,803 $1,039 $179 $194 $421
≥50 38 10.3 $1,360 $1,205 --- $85 $185
Marital
status
Single 88 23.5 $1,601 $1,193 $196 $178 $465
Married 277 74.1 $1,655 $1,020 $164 $175 $378
Dependent
children
Yes 198 73.3 $1,766 $1,047 $180 $174 *$500
No 72 26.7 $1,535 $1,081 $170 $175 *$259
Note: Expenditures are in Australian dollars. The above 50 age cohort category for expenditure on culture/sporting activities
received no response. * denotes significance at 5% level. The test results with respect to small samples need to be treated with
caution.
Chinese holiday makers expenditures Page 36 of 41
36
Table 3
Expenditures by Place of Residence, Education, Occupation, and Income
Social demographic and trip
characteristics N % Expenditure ($)
Total Shopping Cultural/
sporting
Food/
drink
Gambling/
entertainment
Place of
residence
Beijing 55 14.8 $1,299 $848 $159 $221 $313
Shanghai 91 24.5 $1,685 $1,091 $151 $178 $393
Guangdong 70 18.8 *$1,264 $882 $291 $153 $369
Zhejiang 39 10.5 *$2,243 $1,422 $122 $161 $351
Other 117 31.4 $1,807 $1,107 $183 $168 $444
Education ≤Junior school 26 6.8 $1,677 $1070 $333 $238 *$940
Senior school 60 15.8 $1,589 $825 $125 $141 *$191
College cert/diploma 73 19.5 $1,708 $1,246 $150 $267 $426
Undergrad degree 160 42.7 $1,633 $1,032 $182 $138 *$300
≥Postgrad degree 56 14.9 $1,646 $1,030 $162 $168 $469
Occupation
Business owner 94 25.2 $1,840 $999 $162 $136 $275
Manager 95 25.5 $1,971 *$1,424 $223 $206 $330
Professional 49 13.1 $1,420 *$699 $93 *$94 $434
Student 55 14.8 $1,495 $810 $196 $180 $526
Other 80 21.4 $1,243 $940 $175 *$276 $605
Annual
personal
income
≤¥100,000
($16,529)
177 48.6 *$1,346 $948 *$112 $197 $342
¥100,001-300,000
($16,529-49,587)
111 30.5 $1,648 $1,034 *$209 $138 $345
≥¥300,001
($49,587)
76 20.9 *$2,401 $1,294 *$215 $178 $519
Note: Expenditures are in Australian dollars. * denotes significance at 5% level. The test results with respect to small samples
need to be treated with caution. Annual incomes are presented in both RMB (¥) and Australian dollar ($). At the time of the
survey, the average exchange rate was $1 to ¥6.05.
Chinese holiday makers expenditures Page 37 of 41
37
Table 4
Expenditures by Trip Characteristics
Social demographic and
trip characteristics N % Expenditure ($)
Total Shopping Cultural/
sporting
Food/
drink
Gambling/
entertainment
First-time/
repeat visit
First-time
visitor
332 92.2 $1,693 $1,088 $179 $181 *$354
Repeat
visitor
28 7.8 $1,119 $578 --- $126 *$899
Number of
nights in
Australia
≤6 nights 186 57.1 *$1,296 *$763 $146 *$141 *$318
7 to 8
nights
98 28.5 *$2,387 *$1,412 $242 *$259 *$538
≥9 nights 50 14.4 *$1,546 *$1,271 $168 $175 $294
Number of
people
spending
together
1 156 44.3 *$2,126 *$1,469 $174 $224 *$585
2 73 20.7 *$1,536 $997 $184 $136 *$299
3 75 21.3 *$1,350 *$665 $164 $139 $343
≥4 48 13.7 *$840 *$522 $188 $146 *$135
Visitation to
other
destinations
Yes 223 65.6 *$1,802 $1,051 *$147 $174 $433
No 117 34.4 *$1,343 $889 *$242 $161 $324
Note: Expenditures are in Australian dollars. The repeat visitors category for expenditure on culture/sporting activities received
no response. * denotes significance at 5% level. The test results with respect to small samples need to be treated with caution.
Chinese holiday makers expenditures Page 38 of 41
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Table 5
Estimated Regression Model on Total Expenditure Estimated Regression Coefficients
Dependent variable: Natural log total expenditure per person in Australia
Independent variable
Unstandardize
d coefficients
Standardized
coefficients
t Sig. Collinearity
statistics
%
impact
B Std.
Error
Beta (p) Tolerance VIF
Constant 7.793 .479 16.267 .000
Age: 30 to 49 .341 .163 .164 2.099 .037 .566 1.765 38.8
Age: 50 and above .111 .246 .032 .449 .654 .668 1.497
Place of residence:
Guangdong
.222 .241 -.083 .919 .359 .420 2.381
Place of residence:
Beijing
-.453 .246 -.165 -1.840 .067 .432 2.317 -38.3
Place of residence:
Shanghai
-.152 .229 -.065 -.664 .508 .361 2.770
Place of residence:
Other
-.237 .221 -.109 -1.072 .285 .336 2.975
Visiting another
destination
.218 .130 .104 1.681 .094 .905 1.105 23.3
6 nights and under -.334 .187 -.165 -1.792 .075 .410 2.441 -29.6
7 to 8 nights .363 .199 .166 1.826 .069 .420 2.384 40.9
Income: ≤¥100,000 -.468 .181 -.231 -2.584 .010 .431 2.318 -38.4
Income: ¥100,001-
¥300,000
-.364 .178 -.166 -2.042 .042 .526 1.903 -31.6
Overall satisfaction .003 .097 .002 .035 .972 .893 1.119
Travel party size -.333 .060 -.353 -5.584 .000 .866 1.155
Model Summary
R Square Adjusted R Square ANOVA
.299 .254 F (12, 203)=6.621 p=.000
Chinese holiday makers expenditures Page 39 of 41
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Table 6
ANOVA Results for Overall Satisfaction
Expenditure Overall
satisfaction Mean
Std.
error
ANOVA
results
F Sig.
(p)
Total Neutral $2086 $354 5.649 .004
Satisfied $1642 $149
Strongly satisfied $890 $149
Note: Expenditures are in Australian dollars.
Chinese holiday makers expenditures Page 40 of 41
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Table 7
ANOVA Results for Satisfaction with Shopping Expenditure Satisfaction with
shopping
Mean Std.
error
ANOVA results
F Sig.
(p)
Shopping Strongly dissatisfied $1,394 $468 4.257 .002
Dissatisfied $619 $117
Neutral $815 $109
Satisfied $1,416 $175
Strongly satisfied $921 $239
Note: Expenditures are in Australian dollars.
Chinese holiday makers expenditures Page 41 of 41
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Table 8
Summary Table of the Effects of Socio-demographics and Trip Characteristics Total Shopping Cultural/
sporting
activities
Food/
drinks
Gambling/
entertainment
Income √ X √ X X
Gender X X X X X
Age √ X X X X
Dependent child X X X X √
Place of residence √ X X X X
Occupation X √ X √ X
Marital status X X X X X
Level of education X X X X √
Travel party size √ √ X X √
Length of stay √ √ X √ √
First/repeat visit X X X X √
Visiting other destination(s) √ X √ X X
Satisfaction √ √ -- -- --
Expenditure Variable